Structural Equation Modeling Using SAS®
BSE1 : BSE41
This course introduces the experienced statistical analyst to structural equation modeling (SEM) in the CALIS procedure in SAS/STAT software. The course also introduces the PATHDIAGRAM statement in the CALIS procedure, which draws path diagrams based on fitted models.
Structural equation modeling is a statistical technique that combines elements of traditional multivariate models, such as regression analysis, factor analysis, and simultaneous equation modeling. These models are often represented as matrices, equations, and/or path diagrams and can explicitly account for uncertainty in observed variables and for estimation bias due to measurement error. Competing models can be compared to one another, providing information about the complex drivers of the outcome variables of interest. Many applications of SEM can be found in the social, economic, and behavioral sciences, where measurement error and uncertain causal conditions are commonly encountered. This course does not address models containing categorical endogenous variables or multilevel SEM, as these methods are not supported in the CALIS procedure.
Structural equation modeling is a statistical technique that combines elements of traditional multivariate models, such as regression analysis, factor analysis, and simultaneous equation modeling. These models are often represented as matrices, equations, and/or path diagrams and can explicitly account for uncertainty in observed variables and for estimation bias due to measurement error. Competing models can be compared to one another, providing information about the complex drivers of the outcome variables of interest. Many applications of SEM can be found in the social, economic, and behavioral sciences, where measurement error and uncertain causal conditions are commonly encountered. This course does not address models containing categorical endogenous variables or multilevel SEM, as these methods are not supported in the CALIS procedure.
Learn How To
- explain a regression model in terms of a structural equation model
- compare results from the REG and CALIS procedures
- produce a path diagram of your model results
- customize a path diagram
- specify models and evaluate model fit in the CALIS procedure using the PATH input style
- specify mediation models and test for complete and partial mediation
- perform complex path analysis
- perform confirmatory factor analysis
- specify general latent variable models
- perform robust estimation for data with outliers
- perform full-information maximum likelihood estimation for incomplete data
- perform honest assessment to validate models.
Who Should Attend
Most appropriately, social, behavioral, economic, and health researchers interested in fitting complex path models and latent variable models
Prerequisites
Before attending this course, you should
- have a strong background in regression modeling
- be familiar with factor analysis
- be familiar with the concepts taught in Statistics 2: ANOVA and Regression or have equivalent knowledge.
SAS Products Covered
SAS/STAT
Course Outline
Terminology and Concepts
- introduction
- simple linear regression
- terminology
- introduction
- PATH input
- path models overview
- mediation models
- assessment of model fit
- model validation
- covariance matrices as input
- confirmatory factor analysis
- leverage diagnostics and robust estimation
- general latent variable models
- handling missing data
- nonnormal data
- further study
Live Class Schedule
Duration: 14 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.